class_docstr: Swap-in HDF5 File Handler.
class_docstr_tok: ["Swap-in","HDF5","File","Handler","."]
code: def _get_data(self, num_scans, num_cols):
      data = {
          "Data/resolution_1km/Solar_Zenith_Angle": xr.DataArray(
              da.ones(
                  (num_scans * 4, num_cols * 4),
                  chunks=1024,
                  dtype=np.uint16,
              ),
              attrs={
                  "scale": 0.01,
                  "offset": 0.0,
                  "fill_value": -999.0,
              },
              dims=("x", "y"),
          ),
          "Geolocation/resolution_1km/Latitude": xr.DataArray(
              da.ones(
                  (num_scans * 4, num_cols * 4),
                  chunks=1024,
                  dtype=np.uint16,
              ),
              attrs={
                  "scale": 0.01,
                  "offset": 0.0,
                  "fill_value": -999.0,
              },
              dims=("x", "y"),
          ),
          "Geolocation/resolution_1km/Longitude": xr.DataArray(
              da.ones(
                  (num_scans * 4, num_cols * 4),
                  chunks=1024,
                  dtype=np.uint16,
              ),
              attrs={
                  "scale": 0.01,
                  "offset": 0.0,
                  "fill_value": -999.0,
              },
              dims=("x", "y"),
          ),
          "Data/resolution_1km/Radiance_01": xr.DataArray(
              da.ones(
                  (num_scans * 4, num_cols * 4),
                  chunks=1024,
                  dtype=np.uint16,
              ),
              attrs={
                  "scale": 0.01,
                  "offset": 0.0,
                  "fill_value": -999.0,
                  "F_solar_constant": SOLCONST,
              },
              dims=("x", "y"),
          ),
          "Data/resolution_4km/Solar_Zenith_Angle": xr.DataArray(
              da.ones(
                  (num_scans, num_cols), chunks=1024, dtype=np.uint16
              ),
              attrs={
                  "scale": 0.01,
                  "offset": 0.0,
                  "fill_value": -999.0,
              },
              dims=("x", "y"),
          ),
          "Geolocation/resolution_4km/Latitude": xr.DataArray(
              da.ones(
                  (num_scans, num_cols), chunks=1024, dtype=np.uint16
              ),
              attrs={
                  "scale": 0.01,
                  "offset": 0.0,
                  "fill_value": -999.0,
              },
              dims=("x", "y"),
          ),
          "Geolocation/resolution_4km/Longitude": xr.DataArray(
              da.ones(
                  (num_scans, num_cols), chunks=1024, dtype=np.uint16
              ),
              attrs={
                  "scale": 0.01,
                  "offset": 0.0,
                  "fill_value": -999.0,
              },
              dims=("x", "y"),
          ),
          "Data/resolution_4km/Brightness_Temperature_09": xr.DataArray(
              da.ones(
                  (num_scans, num_cols), chunks=1024, dtype=np.uint16
              ),
              attrs={
                  "scale": 0.01,
                  "offset": 0.0,
                  "fill_value": -999.0,
              },
              dims=("x", "y"),
          ),
      }
      return data
  
file_path: satpy/satpy/tests/reader_tests/test_msu_gsa_l1b.py
imports: import os
  from unittest import mock
  import dask.array
  import numpy
  import pytest
  import xarray
  from satpy.tests.reader_tests.test_hdf5_utils import FakeHDF5FileHandler
  from satpy.tests.utils import make_dataid
label_desc: Use image node_id 1 for calling the FakeHDF5FileHandler2 obj's underlying member method code with example usage: obj._get_data(num_scans, num_cols) and returns: data